M. Lebreton

Neural and computational underpinnings of biased confidence in human reinforcement learning

This study combines fMRI and reinforcement learning to show that the VMPFC encodes a task-wide confidence signal influenced by valence, distinct from dorsal prefrontal networks.

Targeted genomic sequencing with probe capture for discovery and surveillance of coronaviruses in bats

This study uses hybridization probe capture to improve genome recovery from bat coronavirus specimens, identifying novel viruses and achieving higher sequence coverage than standard methods.

Wildlife in Cameroon harbor diverse coronaviruses including many isolates closely related to human coronavirus 229E

The paper identifies diverse coronaviruses in Cameroon wildlife, including HCoV-229E-like viruses in bats, and highlights ecological factors influencing their circulation.

Coronavirus surveillance in Congo basin wildlife detects RNA of multiple species circulating in bats and rodents

The paper surveys coronaviruses in Congo Basin wildlife, finding RNA in 121 animals, mostly bats, with some sequences closely related to human coronaviruses.

Coronavirus surveillance of wildlife in the Lao People's Democratic Republic detects viral RNA in rodents

The paper detects Betacoronavirus RNA in 12 rodents from Laos, belonging to two genetic clusters related to regional rodent coronaviruses and distantly to human coronaviruses.

Robust Pavlovian to Instrumental and Pavlovian to Metacognitive Transfers in human reinforcementlearning.

This study investigates valence effects in reinforcement learning, finding robust Pavlovian-instrumental transfer (PIT) and Pavlovian-to-metacognitive transfer (PMT) effects that persist despite attempts to disrupt them.

Cell-free DNA Reveals Potential Zoonotic Reservoirs in Non-Human Primates

The paper uses cell-free DNA sequencing to identify microbial taxa in non-human primates, revealing potential zoonotic pathogens and their association with host species.

Contextual influence on confidence judgments in human reinforcement learning.

This study shows participants are more confident in gain-based decisions than loss-based ones, despite equal difficulty and performance, suggesting a domain-general bias influenced by context-value.

Reference-point centering and range-adaptation enhance human reinforcement learning at the cost of irrational preferences

This study investigates reinforcement learning by manipulating outcome valence and magnitude, finding that reference point dependence and range adaptation improve learning but lead to irrational choices in new contexts.

Two sides of the same coin: monetary incentives concurrently improve and bias confidence judgments.

This study shows that monetary incentives improve confidence accuracy but also bias confidence reports, affecting how confidence is formed from perceptual evidence.